Begin |
|
(1) Initialize the colony . |
(2) Construct by solution space transformation. |
(3) Obtain the optimum solution of the current among and the current optimum chromosome among |
by evaluating . |
(4) Store into and into . |
While (not termination-condition) |
Begin |
|
(5) Calculate by updating and mutating the states of . |
Determine by solution space transformation. |
(6) Obtain the optimum solution of the current among and the current optimum chromosome among |
by evaluating . |
(7) If |
; |
Otherwise |
; |
End |
End |
End |
(8) The procedure of FCQIEA can be summarized as follows: |
Step 1. Initialize the population. Let the current generation ; generate an initial |
population , which has individual qubits. Set the magnitude of the rotational angle , |
, and , respectively. Set as the mutation and as the maximum generation. |
Step 2. Transform the solution space. Four approximate solutions in each chromosome are transformed from the unit space |
to the solution space of the continuous optimization problem (1); thus, the set of approximate solution |
can be obtained. |
Step 3. Compute the fitness. By computing the fitness of approximate solutions, obtain the best solution in the |
current solution and the best chromosome in the current chromosome. Store as the global optimum solution |
and store as the global optimum chromosome . |
Step 4. Set . Update and mutate . Calculate the new population . |
Step 5. Transform the solution space again and obtain a set of approximate solution . |
Step 6. By computing the fitness of , determine the current optimum solution and the current optimum. |
chromosome If , then update the current optimum solution ; at the same time, |
update the current optimum chromosome to avoid population degradation. Otherwise, let |
and so that the algorithm approaches the global optimum solution. |
Step 7. If the algorithm does not converge and if , then go back to Step 4 until the algorithm |
becomes convergent or until . |